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胃癌映射算法的开发:将 EORTC QLQ-C30 和 QLQ-STO22 翻译为 EQ-5D-5L 卫生实用设施

Huali Zhou¹, Xianxi Liu², Rong Bao¹

¹Department of Gastric Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.

Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation

|September 13, 2025

概括

这项研究开发了一个模型来估计胃癌患者的EORTC QLQ-C30和QLQ-STO22分数的EQ-5D-5L健康实用程序. 这允许在缺少EQ-5D-5L数据的情况下进行成本效益分析.

科学领域:

卫生经济学卫生经济学
在瘤学瘤学.
心理测量心理测量心理测量

背景情况:

欧洲癌症研究和治疗组织的生活质量问卷 (EORTC QLQ-C30) 和EORTC QLQ-STO22被广泛用于评估癌症患者的生活质量.
欧科尔5维5级 (EQ-5D-5L) 是衡量健康结果的标准化工具,对于成本效益分析至关重要.
需要从 EORTC QLQ-C30/QLQ-STO22 直接映射到 EQ-5D-5L,以方便在 EQ-5D-5L 数据不可用时进行经济评估.

研究的目的:

开发和验证一个统计模型,将 EORTC QLQ-C30 和 QLQ-STO22 评分映射到 EQ-5D-5L 健康实用值.
评估不同回归模型在从EORTC QLQ-C30/QLQ-STO22数据中预测EQ-5D-5L值方面的性能.
为研究人员提供一个工具,以估计胃癌患者的成本效益分析的健康效用.

主要方法:

在中国大陆的一组1059名胃癌患者提供了模型开发的数据.
皮尔森相关性评估了 EORTC QLQ-C30/QLQ-STO22 和 EQ-5D-5L 之间的概念重叠.
采用了四种回归模型 (OLS,Tobit,Oprobit,Betamix),使用EORTC QLQ-C30/QLQ-STO22维度得分,年龄和性别作为预测因素.
通过随机抽样和五倍交叉验证证实了模型的概括性.

主要成果:

订序探针回归 (Oprobit3) 模型表现出最佳性能,达到0.703.3的R平方.
对Oprobit3模型的关键性能指标包括RMSE=0.197和MAE=0.111.
EORTC QLQ-C30和QLQ-STO22的所有维度以及年龄和性别在最终模型中都是重要的预测因素.

结论:

开发的算法有效地使用EORTC QLQ-C30和QLQ-STO22分数来估计EQ-5D-5L的健康公用事业.
这种映射模型支持胃癌研究的成本效益分析,特别是当没有收集EQ-5D-5L数据时.
这些发现增强了现有的生活质量数据在瘤学经济评估中的有用性.

关键词:

在 EORTC QLQ-C3030 中,在 EQ-5D-5L 中.胃癌是什么?胃癌是什么?在QLQ-STO2222中.响应映射反应的映射.

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